Info for R users (Links, Manuals, Books, etc.)


Debugging Code/Functions

As I develop my code writing I'm in need of debugging techniques. This link (LINK) from Stack Overflow is a great resource for some debugging options.


I just picked up a book from the university library called ``Data Mining With R'' by Luis Torgo. It's by no means a begginers book but for a mid skilled R user the book has some nice explanations. I've never really gotten into imputation (in my field missing values are usually deleted listwise; but why? That's garbage if you've got techniques that may be appropriate) but this book has a chapter introducing the topic in a pretty elementary way. I'm only on chapter 3 but have loved it thus far. The explanation of tree models and pruning is quite nice.
If you're into data mining or have wanted to learn more about it I'd definitely recommend this book.


Probably A Mammal
Looks like biola university has a copy available in my interlibrary loan program. Hopefully I can get it in the next week or so!

Imputation is important. I created a wrapper for R's interpolation function to use spline interpolation to fill in missing data points in some pollutant monitoring data I had. It was a nice touch to have a complete graph, and since it was continuous with minimal missing values, the interpolation was appropriate. (Though, I ended up putting a smoother on the line anyway.) In any numerical analysis program, you usually go over interpolation methods. There are quite a few options in that regard, and I'm sure there's other cases where other imputation methods I'm unaware of are more appropriate. I look forward to checking this book out! Need new gym bike material to read haha


Ambassador to the humans
Would there be any objection if I went through this thread and consolidated the links into the initial post by Tart? I would add a note at the beginning of the post mentioning that the OP is being updated.
If you are learning R and already know another package, R for SAS and SPSS Users or R for Stata Users will take advantage of what you already know and translate that into knowledge of R. The table of contents and index lets you look things up by what SAS / SPSS / Stata would call something or what R calls it. You can read reviews of it at

There are also lots of examples of things done in R, SAS, SPSS and Stata at
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Your books are how I got into R and how I now teach others. Lovely to have you on board Bob!
That's great to hear! As anyone who writes technical books will tell you, you can make way more money flipping hamburgers for minimum wage. So it's always encouraging to hear people find my books useful. Thanks, Bob


Ambassador to the humans
This is more for programming in general but... if you've ever wondered why things like this happen:

> a <- sqrt(2)
> a*a == 2
You should probably read this:

It's not terribly short but is very useful for anybody doing any sort of computation using floating point arithmetic.